Diversification is one of the central tenets of investment management and fundamental beliefs across the global financial planning industry. Its validity was set in stone by Harry Markowitz in his PhD dissertation and 1952 Journal of Finance article, Portfolio Selection, which demonstrated the effects of combining uncorrelated assets … i.e. improvement in the portfolio’s return …

The following article was published by Professional planner Magazine a couple of months ago and whilst can be found on their website by clicking here … the original article follows. Background One of the biggest trends in the financial planning today is the shift towards managed accounts. This is primarily an exercise in increasing efficiencies …

Background For quite a few years now, many commentators and researchers have criticized active strategies that charge active fees to receive benchmark-like returns. If a portfolio looks a lot like the benchmark it is trying to outperform, it doesn’t mean there won’t be outperformance, but after taking fees into consideration it is much more difficult. …

The following article was first published in the August Professional Planner magazine and can also be found on their website by clicking here … otherwise just read on … The management guru, Peter Drucker, is attributed with the phrase, “you can’t manage what you don’t measure” and whilst we know that is not completely true, …

Professional Planner magazine published the following in their June Magazine and also on their website … you can also click here. Otherwise … read on … On the first Friday in May, the Chief Investment Officer of the Future Fund, Raphael Arndt, spoke about how they are refining their approach to their listed equities investment …

Diversification is one of the central tenets of investment management and fundamental beliefs across the global financial planning industry. Its validity was set in stone by Harry Markowitz in his PhD dissertation and 1952 Journal of Finance article, Portfolio Selection, which demonstrated the effects of combining uncorrelated assets … i.e. improvement in the portfolio’s return per unit risk. This showed diversification to be the closest thing to the Holy Grail of investing and possibly the only “free lunch” (Rebalancing may be the free dessert) as it was possible to improve the return expectation of a portfolio without necessarily increasing risk (or vice versa … maintaining the expected return whilst decreasing risk).

Whilst, today, the concept of diversification may seem second nature to all of us in the investment industry, some of its fundamentals are often misused and sometimes misrepresented. Diversification is probably the most commonly used justification for investment recommendations and the word carries a sense of lower risk which is always appealing. Unfortunately some of its use appears to have shifted from Modern Portfolio Theory (MPT) definitions, originated by Markowitz, William Sharpe, et al., towards potentially misleading ways which may confuse.

The purpose of this article is to return to some of the (forgotten?) foundations of diversification, and hopefully address potential misconceptions or misunderstandings.

A simple example

It is not uncommon for investment advisers to recommend a portfolio that improves an investor’s existing portfolio on the basis of greater diversification. A simple example may be the investor who has a lot of their wealth tied up in a single stock, maybe because of an employee share scheme or inheritance, etc. The adviser would be concerned about the concentration risk of this single stock and would recommend a sell-down or reduced exposure to the stock to spread its risk across a portfolio of managed funds or perhaps a larger stock portfolio. The justification is the greater diversification because risk has been reduced away from the single stock to a broader portfolio and this has not necessarily compromised return potential.

This may be quite a valid recommendation with a valid justification. Spreading the risk from one stock to many others is a simple example of diversification but there is a little more to this than meets the eye…

Measuring Diversification

Modern Portfolio Theory (MPT) defines the completely diversified portfolio as the Market Portfolio. Without going into too much explanatory detail, because the Market Portfolio contains all assets, the market cannot be diversified away (except, by other markets). So increasing diversification is an exercise in shifting a portfolio to be more market-like. In the “simple example” this was a shift from the specific risk of one stock to many more stocks.

This all means that to measure the level of diversification of a portfolio, consistent with MPT, means it should be measured in the context of the market or market risk. Measures commonly used include active share, tracking error, or systematic risk as defined by the R-Squared of the Capital Asset Pricing Model (CAPM).

Using the CAPM R-Squared measure, an index portfolio is close to 100% market risk, and active strategies will have variable market risk depending on how active and how diversified or concentrated they intend to be. The active strategy’s obvious goal is to ensure that non-market risk produces excess risk-adjusted returns (“Alpha”), but they will always have less diversification than the market.

As examples, the following three charts show the market (blue) and non-market risk (green) through time (using Markowitz defined risk) for:

an Australian Equities index fund

Popular actively managed Australian Equities fund, and

Popular actively managed small-cap Australian Equities fund

Source: Delta Research & Advisory

The index fund, as expected, is all blue and therefore all market risk; the active strategy is dominated by market risk but with a substantial proportion of non-market risk (sometimes called active or idiosyncratic risk), and the restricted Small Cap strategy, expectedly, has an even higher proportion of green (or non-market risk) as it excludes the large-cap stocks from the market.

So when recommending changes based on diversification, it is possible to explicitly measure and demonstrate the changes and/or improvement in diversification using past performance risk measures.

Diversification Misrepresented

Many may argue that investment recommendations are sometimes looking to diversify away specific risks, as opposed to non-market risks, which may not result in the portfolio becoming more market-like. A popular example, is where an adviser recommends a Small Cap Australian Equities strategy to diversify away the large cap bias of the Australian equities market which is dominated by large banks and materials companies. Whilst, on the surface, this justification appears reasonable there are some issues of which advisers need to be aware.

Firstly, this is not diversification, but is actually the opposite.

Considering the first step of portfolio construction is Asset Allocation, which is designed based on market expectations of asset classes (i.e. “Beta”), a recommendation of a small companies strategy restricts the portfolio and therefore increases concentration risks to small caps and away from the market (or beta) recommendation. This shift away from the asset allocation decision potentially increases risks of market relative performance failure (i.e. compared to recommended asset allocation). Don’t forget, complete diversification contains all assets, which the restricted small cap strategy cannot.

The decision to move away from the market, dominated by large caps, is an active decision which is likely to carry the belief that small caps are likely to outperform large caps, so it is a decision designed to outperform the market and generate “Alpha Risk” (similar to tracking error) and therefore not based on diversification. Diversification is actually “Alpha Risk” minimisation. A portfolio that contains a single security is the simplest example of a massive “Alpha” bet whilst an index portfolio contains no “Alpha” bet whatsoever.

Alternatives

For the last 10 to 15 years, Alternatives have made appearances in more and more investment portfolios and often for reasons of diversification. Sometimes this is true and sometimes not. Alternatives can bring diversification benefits to a portfolio by accessing markets that do not exist within a portfolio. This may be true of soft and hard commodities, private equity, and maybe unlisted infrastructure. This is because these asset classes, or markets, are not represented in the traditional asset allocation of bonds and equities. “A market cannot be diversified away”, except by a different market.

Where Alternatives do not diversify but actually increase concentration or non-market risk, is for the various equity and bond strategies executed by many hedge funds. This includes long-short, variable beta, and potentially other arbitrage or concentrated strategies. Including these strategies does not increase diversification, as it is always possible these strategies have the same market exposure as an index fund, but increases the concentration risks linked to the success or otherwise of the specific strategy bets. Like the small cap recommendation, the inclusion of equity or bond “alternatives” is a recommendation based on capturing manager skill (Alpha) and ability to outperform a market and not one based on improving diversification and minimising non-market performance risk.

Quick word on Over-Diversification

Overdiversification is often mentioned amongst investment circles and in a cost-free world isn’t possible. Overdiversification occurs, when the costs of adding securities or investments to a portfolio detract from performance potential due to these costs. When costs are nil or very low, overdiversification is difficult or impossible to achieve.

For example, a portfolio of many index funds for the same asset class will only be detrimental to portfolio returns compared to one index fund if there are flat fees charged per investment. There is no overdiversification because there is no non-market risk to diversify and the return, irrespective of the number of funds, will be the market minus the average of the low management fees. Diversification and return impact is likely to be minimal … although there is rarely any value in having multiple index funds (of the same market).

Overdiversification most frequently occurs when combining active managers of the same asset class. This is because the more active managers in a portfolio, the more they diversify away the portfolio’s non-market risk (because you can’t diversify away market risk), potentially leaving a portfolio that resembles an index fund but at active manager costs. Measuring this is possible using historical data as already discussed and shown with Figures 1 through 3, but predicting the optimal number of strategies is difficult and can vary depending on how active and correlated each strategy is.

Final Thoughts

It seems diversification is used to justify more than it should. Diversification is a free lunch but only in the context of the market portfolio. It ceases to be free when concentration and greater specific risks are introduced. Diversification is a relative concept and is about reducing non-market risks and not increasing market outperformance potential.

There is no right or wrong level of diversification as there are many schools of thought and examples with reasonable evidence as to what works in markets and what doesn’t. Warren Buffet is quoted as saying that “Diversification is ignorance” and yet recommends most should invest in index funds. Lower levels of diversification may be safest when investment skill exists, but finding true skill is difficult, sometimes expensive, and persistent skill is rare.

Investment recommendations are designed to reflect one’s investment philosophy which help an investor achieve their financial goals. If you believe markets are efficient, you have defined the appropriate level of diversification, and will recommend market portfolios. If not, the portfolio construction question to be answered is, how much diversification is enough?

The following article was published by Professional planner Magazine a couple of months ago and whilst can be found on their website by clicking here … the original article follows.

Background

One of the biggest trends in the financial planning today is the shift towards managed accounts. This is primarily an exercise in increasing efficiencies and lowering costs to serve clients, but it also has created other risks and shifted the financial planner closer to the role of fund manager. Whilst financial planners have always managed client investment portfolios, the managed account trend towards becoming more like fund managers requires a different set of skills, knowledge, and risks, that come with discretionary portfolio management.

The purpose of this article is to provide a guide to one of the foundations of quality funds management and to aid in this shift towards a more professional approach to all things investing … the Investment Policy Statement (IPS).

What is an Investment Policy Statement (IPS)

An Investment Policy Statement defines the rules of investment portfolio management. That said, it can easily apply to all investment decisions whether it be model portfolios, construction of approved product lists, or the management of a self-managed superannuation fund. Establishing a comprehensive IPS, irrespective of purpose, is a step towards stronger risk management and governance of all investment businesses whether implementing managed accounts or traditional investment advice approaches.

Chart 1 shows one version of the structure of an IPS. Central to the IPS are the objectives, with surrounding components designed to maximise the achievement of those objectives. Namely, Philosophy, Process, Implementation and the Ongoing Review. Covering all aspects of the IPS is a system of Governance focused on execution and accountability of all policies. Following are descriptions of each of these components. Please note, this article does not provide a comprehensive description of everything involved in the design and execution of the IPS and serves as an initial guide to lay the foundations towards better investment decisions and ultimately, investment portfolios.

Governance

Across the investment industry, the governance function is usually performed by the Investment Committee which is a specialist sub-committee of the business’s Australian Financial Services License (AFSL). The Investment Committee owns the IPS, is responsible for its creation, and ensures it is executed accordingly. Whilst there may be portfolio management, analysts, external consultants, and/or an internal Research department, the investment committee’s responsibility is to hold them accountable for the day-to-day running of investment activities.

The investment committee is typically established by way of an investment committee charter, that may for part of the IPS, that outlines the following:

Committee membership and voting rights. This may include:

Senior management

Compliance/Legal/Risk Management representation

Portfolio Management

Independent experts

Committee purpose – Ownership and implementation of the IPS which includes:

Strategy development

Due diligence procedures for investment selection

Investment performance review

Sometimes operational finance and business development review

Meetings are typically quarterly

Minutes and all procedures are documented

Investment and portfolio decisions are documented and communicated appropriately to stakeholders (advisers, staff, and investors)

The committee should ideally review the overall IPS on, at least, an annual basis

The investment committee plays the most crucial role of IPS due to its role in accountability and execution. So, whilst a well-functioning investment committee is no guarantee of strong investment returns, it is a leading indicator of a firm with a strong risk management culture which should reduce the likelihood of left-field investment disasters. Similarly, whilst an IPS may look good on paper, unless its rules and procedures are adhered to, it becomes worthless and a risk to any investment-related business.

Objectives

Central to all investment decisions are the objectives. All investment decisions should be made with consideration of objectives and they should be defined based on the SMART principle:

Specific … may be absolute, such as 8%pa, or relative to a benchmark, such as to outperform the S&P/ASX200 by 2%pa over 3 years

Measurable … this seems simple enough as all investments produce performance, but when cashflows are involved it does get a little more complex and portfolio performance measurement is not perfect across managed account platforms, particularly with respect to Global Investment Performance Standards.

Achievable … Equity markets have outperformed cash and bonds in Australia by no more than 4%pa over the last 50 years. Aiming for high returns may be appealing to potential investors but if they are too ambitious and therefore not achievable, based on the investment strategy employed, then credibility and ultimately business may be at greater risk

Realistic … an achievable return objective does not mean it is realistic; particularly over the long term. For example, a 10%pa return objective may be achievable in any one year across most asset classes, but in this world of low interest rates and historically high valuations, setting any expectation that a consistent 10%pa can be achieved is not realistic and is setting up for failure

Time related … the more aggressive the return objective the more time may be required to achieve it due to the additional risk required. All investment objectives must be associated with a timeframe and rarely should that timeframe be less than 3 to 5 years unless dealing with lower risk strategies (such as conservative bonds)

More and more investment strategies are also including risk in their investment objectives. Risk can have multiple definitions, whether it is absolute (such as overall volatility) or relative (such as less risk than the S&P/ASX 200). It is worth noting that risk objectives should also follow the SMART principles as opposed to being vague, such as motherhood statements like, “low risk”.

Philosophy

The Investment Philosophy is an articulation of beliefs around what works and perhaps what doesn’t when it comes to investing. Investment markets are difficult to predict, highly competitive, and party to an array of beliefs and competing philosophies battle each other in the various markets with the goal of getting the best possible return.

The investment philosophy of a strategy or portfolio is typically what an investor is buying into. This is because the future is largely unpredictable so clear articulation of an Investment Philosophy can be a powerful client tool as well as setting guiding principles behind portfolio construction.

The Australian financial planning industry has embraced much of modern portfolio theory with core beliefs such as:

Diversification … spreading your eggs across the various baskets which may be asset classes, investment styles, and at the security level, and

Higher risk is required to achieve higher returns … hence there is the expectation that equities will outperform cash and bonds.

However, even these beliefs are challenged with strategies around increasing return potential from less diversification and more concentrated strategies. Then there is the market anomaly in certain markets that buying lower volatile securities having a tendency to outperform the more volatile or risky securities, which challenges the second belief around higher risk is required for higher return.

Irrespective of your belief around diversification and risk, the first question of philosophy typically comes down to a belief as to whether passive or active management is best, and whether it is applied to asset allocation, or security selection and in what asset classes.

Some of the more recent beliefs that are changing investment portfolios around the world include passive style investing (commonly called smart beta) and the re-embracing of skill as investors move away from traditional markets towards broader scope hedge fund-like strategies. On the flipside of this has been the biggest trend of all, which has seen enormous funds flow into passive market-cap index ETFs, suggesting many have stopped believing that active management can add value.

The best investment portfolios will have a clearly articulated investment philosophy which is understandable by investors, has evidence to support it, and is reflected in the chosen investments within. If an investor agrees with the investment philosophy, and the portfolio clearly reflects this, then investors are more likely to stay the course and are less likely to withdraw during the tough times that inevitably hit every investment portfolio.

Process

This is the portfolio construction process and leading to the ultimate design of the investment portfolio. It is designed to achieve the stated objectives, and reflects the stated investment philosophy or beliefs around what works in markets. An example of some of the questions to answer in the process design include:

What is the investment universe?

Which asset classes are included or excluded?

Which securities or investment types are included or excluded?

What is the expected return and risk of those asset classes or investments within the universe?

Depending on methodology this question may also include the more complex relationship between asset classes or investments (e.g. correlation or covariance)

What are the investment vehicles used to access the investment universe?

This could relate to:

Platform availability/limitations

AFSL limitations such as limited products (managed funds, securities)

What are the required hurdles to be placed in the final portfolio?

Qualitative factors

Philosophy, People, Process

Quantitative factors

Performance, risks, style, added value (past/expected)

Research/Consultant ratings

Expected returns and/or returns/risk

Alignment with philosophy

Cost budget

Risk Budget

The above is a relatively simple snapshot of some of the questions that could be answered to build the investment portfolio.

An investment philosophy with beliefs around market efficiency will lead towards passive index investing and beliefs of market inefficiency will bias strategies with various levels of non-market risk. Whilst this is relatively easy at the investment level, defining the “market” at the asset allocation level is rarely done and is often accepted as an industry average.

Investment objectives and philosophy will determine the type of process required which should also improve the efficiency of the design of the final investment portfolio. That said, implementing the investment process towards portfolio does require the greatest level of specialist investment expertise so its design should also consider capabilities of the key people involved.

Implementation

The execution or transaction of the investment portfolio is often one of the most overlooked components of the investment process. Considerations include:

Cost of execution

Buy/Sell spreads or brokerage can be significant return reducers irrespective of the quality of underlying assets that may reduce the ability to achieve objectives. This is particularly the case for high turnover strategies

Managed account platforms may reduce costs of execution compared to other platforms when implementing complimentary strategies. For example, if one strategy is buying BHP whilst the other is selling BHP instead of 2 independent transactions there may be none or a reduced transaction savings numerous valuable basis points in cost

Timely execution

Portfolio return and risk expectations are made at a specific point in time and the time taken between the investment decision and time of execution may be costly

Some investments, such as IPOs or various corporate actions, have deadlines, and if they are not addressed appropriately may also have costly implications.

Rebalancing (which may also be part of Process)

Establishing clear rules around rebalancing, whether it be at the asset class level, investment level, frequency (e.g. quarterly or annually), and/or movement from desired allocations (e.g. +/-10%) creates transparency and clarity for appropriate execution of the ongoing investment management of an investment portfolio

Overall, good portfolio implementation with clear rules can add return via the reduction of performance drag caused by poor implementation. When decisions are made to invest today based on today’s information, ideally investments are transacted today instead of adding the risk of short term market timing which has very little evidence of adding value. Implementation guidelines should not be taken for granted.

Ongoing Review

The one constant about investing is that nothing is constant. Markets go up and down, styles go in and out of favour, beliefs are constantly challenged, and every investment or investment manager underperforms their objectives or benchmarks at one time or another.

The ongoing review looks at the portfolio with typical outcomes focused on:

Ensuring the portfolio is aligned to meet objectives and a reflection of investment philosophy

Is the asset allocation appropriate?

Capital market views and valuation considerations

Investment and Performance review

Are the investments doing what they are expected to do so?

Are investments still satisfying required ratings?

Are they invested according to stated styles?

Are the drivers of portfolio returns and risks aligned with intentions?

The answers to these questions re-start the portfolio construction cycle leading to new portfolio recommendations (which may be to do nothing) and the cycle continues.

Whilst investment teams will consider portfolios on a daily basis, the formal review presented at the investment committee and typically on a quarterly basis. That said, the frequency of the formal portfolio review should depend on investment style and/or level of expected activity. Sometimes portfolio reviews are undertaken more frequently, and many are monthly. An example, may be during highly volatile times when market valuations fluctuate and potentially creating opportunity for the highly active strategy.

One of the challenges of the ongoing review is to avoid shot-termism. Changes in monthly or quarterly (or even annual) performance is often too short a timeframe to make a meaningful assessment of the potential success of an investment or portfolio of investments as styles that are out of favour today may be in favour tomorrow (and vice versa). It is typically best to keep an eye on the bigger picture issues such as ensuring the portfolio is a reflection of beliefs than persistent alpha (or outperformance) generation.

Conclusion

What this article provides is a starting point for those looking to improve the risk management of their investment business. The IPS is a key part of all successful investment management businesses from the largest Sovereign Wealth funds to the smallest boutique fund managers or advisory firms. Creating the rules of the investment game, with IPS, is a step in the right direction of good governance and risk management that is becoming even more crucial in these increasingly complex investment times.

Background

For quite a few years now, many commentators and researchers have criticized active strategies that charge active fees to receive benchmark-like returns. If a portfolio looks a lot like the benchmark it is trying to outperform, it doesn’t mean there won’t be outperformance, but after taking fees into consideration it is much more difficult. Taking larger position that are different from the benchmark will provide a portfolio manager with more opportunity to add alpha (risk-adjusted return) but at the same time, if those bets are wrong, then there is greater negative alpha potential too.

So, a popular portfolio construction method of many multi-manager portfolio constructors is to build portfolios of strategies which have greater idiosyncratic (or non-market) risks. The hope is to create greater alpha potential for their portfolio by avoiding the benchmark huggers, and at the same time diversify away various manager risks with the multi-manager approach. Sound reasonable? Well it does, unless you end up building the same type of portfolio you are trying to avoid.

Ultimately portfolio construction is about the efficient capture of risks we believe will add value and the avoidance of risks we believe won’t add value. Combining highly active strategies is about capturing idiosyncratic risks of an active manager in the hope positive alpha is created. What is sometimes forgotten is that market risk cannot be diversified away (except by other markets) and the diversification of strategies may diversify away the idiosyncratic risk you may be trying to capture.

Idiosyncratic Risk vs Alpha

Idiosyncratic risks are non-systematic risks of a portfolio. In the context of equities, those systematic risks include the market (e.g. S&P/ASX 200 or MSCI Australia), and perhaps various other systematic risks commonly called factors such as Value, Size, Momentum, et al.

We pay active managers the higher fees to turn idiosyncratic risk or these non-systematic bets into positive returns (otherwise known as positive alpha). But how much idiosyncratic risk is normal?

Chart 1 below breaks up total portfolio risks of all active strategies in the Australian market over the last 10 years into various systematic risks as well as idiosyncratic risk (green). It shows that over the last 10 years, the average idiosyncratic risk of all strategies (equal weighted) has been between 5% and 10% of total portfolio risk on a rolling 3 year basis with the dominant component being the market, which caters for around 85% to 90% of total portfolio risk. The other components of risk in this analysis come from a variety of factors which are important but are not the focus on this article.

Chart 1 – Portfolio Risk of Active Australian Equity Strategies

So the simple conclusion from this piece of analysis is that the market is easily the major component of active strategy’s total risk and this is consistent with numerous studies of long only strategies … including Brinson, Hood and Beebower (1986), who showed that more than 90% of the portfolio risk came from the asset allocation decision (or market allocation decision).

Basically, if a strategy is long only, then market risk is going to play a significant role in the portfolio outcomes and on face value, and the alpha potential comes from a much smaller component of a portfolio’s risk.

Chart 2 – CAPM Alpha vs Market Risk Contribution

Chart 2 shows the relationship between Idiosyncratic and Alpha for Active Australian Equity strategies over the last 5 years.

Whilst Chart 2 as a whole does appear to be a fairly random, the line on the chart is placed to show that there may be a relationship between maximum Alpha and idiosyncratic risk. Basically maximum alpha appears to diminish with decreasing idiosyncratic risk. The chart also may suggest that the lower the idiosyncratic risk, the lower the spread of Alpha, potentially supporting concerns about Benchmark huggers not producing high enough Alpha but also avoiding negative alpha, which many in the past have suggested relates to minimising career risk, but I digress.

An Experiment – with a Portfolio of Highly Active Strategies

So, to demonstrate some of the effects of building a portfolio of highly active strategies I have conducted a simple experiment.

Using the Delta Factors database of actively managed strategies, I chose five strategies that each produced positive Alpha over the last 5 years, had high levels of idiosyncratic risk (i.e. more than 15% of total portfolio risk). I would imagine this is a relatively common approach. That is, choose the strategy with the best relative performance with some basic appealing characteristics.

The portfolio of strategies, for the sake of simplicity and avoid accidental strategy bias, is equal weighted and rebalanced monthly (and transaction costs are ignored). Table 1 shows the basic market characteristics of five chosen funds.

Table 1 – Active Australian Equity Strategies – June 2012 to June 2017

These five funds, which all appear within the data from Chart1 and 2, have very impressive characteristics, insofar that historically they satisfy what we would typically want from an Australian equity portfolio. That is, they have:

Full exposure to the Australian sharemarket … i.e. Market Beta ~1

Strong value-add … i.e. Average Alpha ~5.1%

Are truly active compared to peers with average Idiosyncratic Risk around 25%

This is obviously historic analysis only over the last 5 years, and we all know the past doesn’t equal the future … but it doesn’t stop of us from hoping. The construction of these highly active funds is about moving away from the benchmark huggers to produce the stronger possibility of high alpha.

So far so good.

Obviously, multi-manager portfolios comprise of more than one manager for each asset class. This is always done for diversification purposes. It may be diversification of styles, managers, or a variety of other risks. What many don’t measure or deeply understand is that a guaranteed outcome of diversification will always be the diversification of Idiosyncratic risk as you cannot diversify away market risk.

As Table 1 shows, this portfolio of active strategies has a historic average of 25% Idiosyncratic Risk. On its own that may be appealing but when they are combined into this portfolio, ignoring rebalancing transaction costs, the Idiosyncratic Risk decreases to 10% … representing a 60% reduction in the very risk we are hoping to capture! The

Now this 60% reduction in risk is specific to the portfolio, and would be lower, if fewer strategies were chosen. Either way, this portfolio of 5 strategies has created is a portfolio with significantly lower idiosyncratic risk than every single component strategy. If there is a belief that greater idiosyncratic risk is required for high Alpha, then this portfolio has significantly reduced that opportunity on a forward-looking basis. The past does not equal the future but it would be difficult to see that this is not a move towards a benchmark-like portfolio … and for highly active fees.

Conclusion

Now many might argue this is just one example and not all combinations of managers will reduce the idiosyncratic risk by this much … and that is absolutely correct. The question becomes, do you know the impacts of the risk characteristics of your multi-manager portfolio? And I would guess many would answer, “no”.

Overdiversification is a common reality in construction of multi-manager portfolios and can result in paying big bucks for more index like returns. But to manage this risk it is essential to measure it. Measuring risk contributions will help constructors ensure the desired risks are being captured more efficiently and can help reduce the effects of desired risks being diversified away. Given the growth in managed accounts across the financial planning industry and the shift towards single strategies for many clients, increased measurement of risks has never been so important for many investors.

Diversification is the only free lunch in investing. Mathematically it is due to less than perfect covariance or correlation as Harry Markowtiz’s Nobel Prize winning paper showed, but better portfolio construction is when you don’t diversify the risk you are trying to capture. That way your free lunch will hopefully taste nice.

The following article was first published in the August Professional Planner magazine and can also be found on their website by clicking here … otherwise just read on …

The management guru, Peter Drucker, is attributed with the phrase, “you can’t manage what you don’t measure” and whilst we know that is not completely true, as we manage numerous tasks without measuring them every day, it is really about defining success. Having a measure of success helps define a goal to achieve and in the world of investment management, success often comes down to performance compared to a benchmark. Whilst most times this is a fairly simple, benign, and obvious issue, there are many examples where benchmarking is done poorly, can be misleading, and ultimately increase risks unbeknownst to the adviser or investor. Individual investors and customised client portfolios of financial advisors rarely have benchmarks.

This article looks at good benchmarking, bad benchmarking, plus a few tricky issues for consideration. An important part of the investment management process is performance analysis, whether up-front during the investment selection step, or during the review phase, and choosing the right benchmark should be integral.

What is a good benchmark?

In essence, a good benchmark is representative of a strategy’s investment universe and is therefore representative of its risk and return characteristics. This means some of the key characteristics of a good benchmark may include being:

Underlying securities and their weights are clearly defined

It is possible to passively invest in the benchmark

Rules behind the creation of the benchmark are clear and frequently calculated

Consistent with intended style or bias

Satisfying these characteristics is often relatively simple with little difficulty in finding suitable benchmarks for most strategies. For example, an Australian equity strategy may be small cap, large cap, or even absolute return focused, but if its mandate dictates that its investment universe is the top 300 stocks listed on the Australian Securities Exchange, an appropriate benchmark may be the S&P/ASX 300 Total Return index. This benchmark is even appropriate for the Small Cap focused strategy if it can invest in larger companies. If the Small Cap strategy is excluded from investing in the top 50 companies, then its benchmark could become the S&P/ASX 300 Total Return excluding the securities from S&P/ASX 50.

Some of the more well-known benchmarks, and their respective asset class, include:

S&P/ASX 200 Total Return – Australian Equities

MSCI World GR – Global Equities

Bloomberg Ausbond Composite – Australian Bonds, and

Bloomberg Barclays Global Aggregate – Global Bonds

Each of these satisfy the above-mentioned criteria required of a good benchmark.

Bad Benchmarks

Unfortunately, there are many strategies using inappropriate benchmarks. The main culprits are often absolute return, credit or high yield debt, and CPI-plus…and/or…pretty much any risk strategy that uses Cash (or CPI) as a benchmark. Cash (or CPI) may well be related to an investment objective, particularly given their definitions as the risk-free rate and the expectation to outperform, however, cash (or CPI) will not be representative of strategy risks.

Similarly, when a strategy invests outside of the investment universe of their benchmark, it may be time for a new benchmark. Investing outside a benchmark may change the risk and return characteristics of the strategy so comparisons can become inappropriate and therefore riskier than realized. Think bond strategies that move up the credit curve and invest in unrated securities, despite having a benchmark that may be cash or investment grade quality.

Cash will always fail the test of a good benchmark for any risky strategy as it will never be representative of the investment universe. The investment industry largely built on the belief that higher risk is required to produce higher return so over the long run, of course risky strategies should outperform cash if that risk is remotely fairly priced; but that does not mean the strategy has exhibited appropriate return or risk to achieve it.

Mixing Benchmarks with Portfolio Construction method

Many strategies will claim they are “benchmark unaware”. Being “Benchmark unaware” has little to do with measuring the success of a strategy and is more a reflection of its portfolio construction methodology. In other words, a “benchmark unaware” portfolio is probably constructed with little consideration of their asset class benchmark, may only hold “best ideas” which are weighted according to conviction of success and not their market capitalization which is a core characteristic of most liquid benchmarks. However, to ascertain whether such a strategy is successful, it is appropriate to measure against a Benchmark that is representative of the investment universe.

For example, an “absolute return” equity strategy may claim to be “benchmark unaware”, with the ability to invest in any equity market in the world. In this case, the benchmark should be more like the MSCI All Countries World Index (ACWI) and certainly not, the frequently seen, cash or cash-plus benchmark. MSCI ACWI will be far more representative of the risk the strategy and if there is likely to be significant cash holdings on a regular basis, then perhaps a strategic or expected level of cash could be included in the benchmark definition. Confusing how a portfolio is constructed does not necessarily change the risk/return profile of a strategy … as risk-adjusted excess return to a traditional benchmark still requires significant skill of a manager no matter the level of active or idiosyncratic risk.

Multi-Manager Problem … can turn into a Multi-Benchmark Problem

Most superannuation funds and financial planners, use a multi-manager approach to designing investment portfolios. Because asset allocation is a key part of the portfolio construction decision, each asset class should be appropriately benchmarked which ultimately frames the underlying manager selection towards strategies that produce the desired asset class characteristics.

Where many investors start to make mistakes (or at least increase risk), is that there is often very little consideration of the asset class benchmark, and strategy selection can become more focused on the strategy’s own benchmark. It is possible to have all underlying strategies outperform their own benchmarks but underperform the asset class benchmark.

One of the more common examples of this is the inclusion of Small Cap Australia Equity strategies as part of the Australian equities asset allocation. Numerous performance analyses over the years have demonstrated outperformance by active managers in the small cap space so the inclusion of these strategies is based on this alpha potential. The fundamental belief is that small caps are a less efficient market enabling active managers to exploit opportunities to produce excess returns. However, what is sometimes ignored is the ability of small caps to produce risk-adjusted outperformance against the asset class benchmark, which may be the S&P/ASX 300 or MSCI Australia index. Alpha amongst Small Caps does not mean Alpha amongst Large Caps.

Another example is Infrastructure. Performance analysis across the Infrastructure suite of products in Australia is often troublesome as it appears almost every strategy has a different benchmark; so understanding whether one strategy is potentially superior to another, can be difficult if looking for outperformance. Different benchmarks between strategies is simply an apples and oranges comparison.

What portfolio constructors must focus on is comparison of strategies to their own asset class benchmark and consideration as to whether a strategy will outperform it. Taking this approach should provide better insights to relative performance behavior and relative risks … apples and apples comparisons are essential for better portfolio construction decisions.

Benchmarks 2.0

With the significant growth in Exchange Traded Funds, Smart Beta, and multi-factor investing, Benchmarking is becoming a multi-layered exercise. Assessing strategies to a traditional asset class benchmark continues to be important, but the separation of determining success (or otherwise) from style or security selection is also important … you should know what you are paying for. Assessing strategies to their own style benchmark enables a deeper understanding of manager capability.

For example, it is widely accepted that a value bias across most equity markets around the world has produced outperformance compared to traditional market-cap weighted benchmarks. Largely thanks to ETFs, it is much easier and cheaper to buy style indices, like Value, so assessing an actively managed value strategy against a value benchmark will go towards understanding whether the manager is skilled at stock selection or is simply successful on the back of the systematic value tailwind. Why pay active fees, if you can get a similar result from a lower cost passive strategy that has the desired style.

What to do?

This article has touched on a few issues around benchmarking and there are many others that can be addressed another time. Either way, there are distinct lessons that can enable better strategy analysis and therefore improved portfolio management decisions. The main lessons this article hgas touched on include:

Choose your own benchmark that reflects the investment universe of the portfolio (or asset class) you are designing

If your investment philosophy dictates a preferred style, then choose a secondary benchmark that is reflective of that style

Assess potential strategies against your chosen benchmark(s) to gain a better understanding of the relative risks, and of course, whether you believe there is outperformance or risk-adjusted value-add potential

If a strategy manages to a different universe and/or a particular style than yours, assessing the manager against benchmarks that reflect their investment universe and/or style can help determine whether they are skilled, maybe lucky, or otherwise; but this is secondary to the desired characteristics of your own measure of success

Ultimately, good benchmarking is simply about creating apples and apples comparisons to better measure success. Comparisons may be return, risk, or a range of other metrics. Be careful of mixing benchmarks with objectives, do not accept benchmarks not reflective of a strategy’s investment universe; and hopefully improved measures of success will lead to more robust portfolio management and better results for investors.

Professional Planner magazine published the following in their June Magazine and also on their website … you can also click here.

Otherwise … read on …

On the first Friday in May, the Chief Investment Officer of the Future Fund, Raphael Arndt, spoke about how they are refining their approach to their listed equities investment program. The primary concern was whether “they are paying for (active) managers stock picking skill”. His view was “if we want factor exposures, we can access factor indices much more cheaply without paying active management fees”. The primary catalyst to this thinking is that the Future Fund faces similar issues to all investors. That is, considering the long-run outlook for investment returns being nothing more than single digits, fees are a very high proportion of the total portfolio expected return so any reduction of fee from increased efficiency will have significant impact on final returns.

As a result, the Future Fund redefined the objectives of their $38billion of listed equities into 4 categories that can be summarised as …

Capturing equity market risk

Harvesting long term equity factor premia

Delivering uncorrelated, good, skill-based returns

Accessing desired exposures with a whole of fund perspective

I’m sure you’ve judged by the title, this article is not about explaining the direction of the Future Fund. The objective of this article is to communicate the benefits of a deeper level of investment analysis than I believe is currently performed across our industry. The reason why I mention the Future Fund’s approach to their listed equities program is that they are the most recent and maybe most prominent example of the application of, what I call, the fourth stage of investment analysis. That said, there is nothing new in the application of the fourth stage but with improving technology, analytical tools, access to a greater depth of breadth of investment strategy, and the financial planning industry’s move towards managed accounts, it is probably time for advised portfolios to take the same step.

Successful application of the fourth stage of investment analysis is likely to increase the move towards designing investment portfolios that have a stronger reflection of our investment philosophy (or beliefs), a more efficient investment allocation, with increased performance risk management.

So what are the Four Stages?

…they are best explained using a graphic as shown in Chart 1.

Stage 1 is pure performance analysis and is what most clients are solely focused on. It is focused on the overall return result and perhaps the volatility. But whilst Performance is typically a primary target, performance numbers alone (or over time) provides little insight as to whether an investment is truly good or bad. Looking only at performance often leads towards bad investment behaviours, such as selling low and buying high.

I would argue that most of the investment advisory community are at Stage 2 which is the assessment of the quality of an investment by comparing to a benchmark … which often concludes that outperformance is good and underperformance is bad. The choice of the benchmark is a critical part of this analysis and where most mistakes are made at Stage 2. Sometimes the benchmark is a peer group which may be fine depending on the investment type but best practice suggests a benchmark should be liquid representation of the underlying investment universe … so is typically a market-cap weighting of available investments. Common benchmarks include the S&P/ASX 200 for Australian equities or MSCI World for global equities.

If we believe that to achieve higher returns requires the acceptance of higher risk, then outperformance alone may be a dangerous way of assessing whether an investment is good or bad. Strategies may have benchmark outperformance over long periods of time, but not because they are necessarily skilful, but because they may be taking on lots of risk. A simple strategy example is a geared Australian Shares index fund … with the Australian sharemarket producing a performance of nearly 11%pa over the last 5 years, an initial loan to value ratio of 50% and borrowing costs at a very high and fixed 5%pa, would have produced returns for the fund in the vicinity of 15%pa. This outperformance has nothing to do with being skilful or good, it’s simply the result of accepting much greater risk than the market.

Chart 1 – Four Stages of Investment Analysis

Stage 3 adjusts for market risk and divides the portfolio’s risk into the two components we hear so much about … alpha and beta. Alpha is the market risk-adjusted outperformance often associated with measures of active management skill; and beta represents a strategy’s exposure to the market. For the above-mentioned Geared Australian Equities Index example, the Alpha should be slightly negative and close to the cost of the fund, whilst the beta (thanks to a Loan to Value ratio of 50%), should be up to 2 … which represents twice the market exposure (or risk). Whilst the geared index strategy has strong outperformance, it’s negative alpha suggests there is no skill because the return has been driven by having double the market exposure.

Understanding an investment’s Beta, or exposure to the market, is an essential part of portfolio construction because this is the measure that helps portfolio constructors determine the asset allocation role of a strategy. If we want to choose an investment that is fully representative then its beta should be around 1. If the strategy’s beta is less than 1 then that strategy may be holding significant amount of cash, so it potentially compromises the desired asset allocation and reduces the portfolio’s goal of capturing the intended “equity risk premium”. A fund with an expected beta of less than 1 will underperform its benchmark in a strong bull market, unless there is significant skill (or alpha) and, of course, that is far from a guarantee. However, that skill may also be due to luck or perhaps styles or factor exposures that happen to be in favour over a period of time. This is where Stage 4 Investment Analysis may be required.

Stage 4 investment analysis is where the Future Fund is at along with many other institutions and sophisticated investment professionals. Stage 4 further adjusts for non-market systematic risks which are typically represented by the Smart Betas that can purchased somewhat cheaply. In English, typical Smart Betas exposures may include style indexes such as Value (e.g. Low PE Ratio), Size (e.g. Small Cap), Momentum (e.g. Last Year’s best performers), Quality (E.g. High Profitability and Low Debt), and others. With the growth of the Exchange Traded Fund (ETF) market into these Smart Beta exposures, purchasing your preferred style of investing is getting easier. As Raphael Arndt of the Future alluded to, purchasing factor exposures is cheaper than pure active management and may sometimes present a more efficient way of gaining desired exposures to reflect your investment Philosophy (or beliefs) around what works in markets.

Stage 4 investment analysis explains which factor exposures (or Smart Betas) are driving portfolio outcomes as well as the exposures to each. This means that the Multi-Factor Alpha (refer Chart 1 – Stage 4) is the pure alpha (or skill) a manager brings to a strategy and is the result of their success in security selection, market timing or potentially, smart beta timing. Positive Multi-Factor Alpha is the holy grail of active management and when you consider the cheaper access of market-cap-weighted index funds, and smart beta funds, positive Multi-Factor Alpha is what investors should be paying the high fees for.

Demonstrates a strategy is “true to label”. That is, the strategy’s market beta and smart beta exposures are consistent with the investment process communicated by the manager

Whilst this is not the end of the portfolio construction or strategy selection process or story, implementing a Stage 4 investment analysis framework is a strong move towards a deeper understanding of portfolio risk drivers.

Understanding likely portfolio risk drivers means potentially greater efficiency as risks can then be accepted, mitigated, or even removed. It changes the manager selection or retention approach to one of return driven to risk driven. This enables strategy roles to be more specifically defined. When executed correctly, portfolios may have lower strategy turnover, therefore reduced investment costs, and therefore better returns.

Perhaps the next steps include answering the questions include … what risks do I believe add value and how do I capture them and remove the ones I don’t believe in? This potentially brings us into the world of factor investing ….

Background

According to (Elroy Dimson, 2010) the “conventional view Is that, over the long run, corporate earnings will constitute a roughly constant share of national income, and so dividends out to grow at a similar rate to the overall economy. This suggests that fast-growing economies will experience higher growth in real dividends, and hence higher stock returns”.

Unfortunately, empirical evidence showing positive relationships between economic growth and sharemarket returns has not been as strong as many have expected and there are many examples, where high economic growth has coincided with terrible sharemarket returns. Emerging Markets and China are possibly one of the better examples of this relationship breakdown in recent years.

The purpose of this article is to revisit the relationship between economic growth and sharemarket returns. Whilst much of the literature, including on this subject focuses on the US, the data presented in this paper also includes Australia and United Kingdom. Why Australia and United? … A couple of reasons and both somewhat naïve. Firstly, they are spread geographically with different major trading partners, and secondly, they were the regions which enabled easiest access to long term data.

Data Sources

For the analysis that follows, all equity market returns are accessed from MSCI database, are calculated in local currency (i.e. AUD for Australia, USD for USA, and Sterling for UK), and data series commence 31/12/1969. The specific indices are MSCI Australia GR, MSCI UK GR, and MSCI USA GR.

Real GDP figures come from each country’s central bank data sources. That is, Reserve Bank of Australia, Bank of England, and Federal Reserve. Please note, at the time of writing Real GDP figures were not available for the December 2016 quarter for either Australia or USA.

Quarterly Analysis

Equity Returns vs Real GDP

Let’s start with a direct comparison of equity returns and real GDP using quarterly data for each country. Figures 1,2, and 3 show the results for Australia, UK, and USA, and only USA shows any relationship. Both Australia and UK show no relationship between equity returns and the same quarter Real GDP results at all…this is supported by the flat trend lines and the R2 result being close to 0.

The USA Trend suggests that for every additional 1% in quarterly Real GDP Growth it correlates with an additional ~2.2% in quarterly equity market returns. With an R2 of less than 5%, Real GDP does produce a great deal of explanatory power of equity returns, but the slope s highly statistical significant given it’s t-statistic is 3.04.

This suggests that of the three countries, if you can predict the quarterly GDP in advance then it might provide a slight edge in the USA only … it doesn’t necessarily help in Australia or the UK.

Is the Sharemarket a leading indicator?

For many the potential spurious relationship between quarterly equity returns and Real GDP is unsurprising because the belief is that the sharemarket is more of a leading indicator, meaning that its direction is a forward predictor of future economic growth. The initial test for this is done by comparing the last period’s equity market returns to the current period real GDP.

The charts and results are shown in Figures 5,6, and 7. Once again, only the USA show a statistically significant trendline suggesting that last quarter’s equity market return might be a leading indicator for this quarter’s Real GDP. That said, the US Equity market return only explains around 10% of the variance in the next quarter’s Real GDP so there is a lot of unexplained variance due to other factors, which should not be surprising.

Neither Australia nor UK show a statistically significant relationship for last quarter’s sharemarket returns being predictive of this quarter’s Real GDP result.

Stretching out the Timeframe … Annual

So far we have looked at quarterly data only and many might argue that it is longer run economic growth that is important to sharemarket returns because quarter-to-quarter can be potentially meaningless due to volatility and the associated uncertainty or potential lack of obvious trend.

Figures 8,9, and 10 show the relationship between annual returns and annual Real GDP and the only significant trend is for the USA. The relationship between annual equity returns and annual Real GDP appears insignificant for both Australia and the UK.

Figure 11 – Regression results for Figure 10’s trend line

Source: Delta Research & Advisory

Interestingly compared to the quarterly results from Figures 3 and 4, there is greater explanatory power in the regression model. Whilst quarterly Real GDP explained around 10% of the variability of quarterly equity returns in USA, annual Real GDP explained more than 28% of the annual equity market variability in USA between 1970 and 2015.

These results show only a stronger relationship over longer term, once again, for USA.

Sharemarket as a Leading Indicator?

So is this year’s sharemarket return likely to provide an indication of next year’s Real GDP Growth? At the quarterly level, there appeared to be potential evidence suggesting the sharemarket might be a leading indicator in the USA only but at the annual level? It is the reverse result. That is, the relationship between lagged annual equity returns and real GDP growth is strong for Australia and the UK and weak for USA…refer Charts 12 through to 14.

In Australia, for every 10% in annual equity returns has meant next year’s Real GDP growth has been 0.383% higher. For the UK, that relationship is similar whereby every 10% in annual returns meant it’s Real GDP was 0.312% higher the following year. Still with R2 of only ~23% and ~15% respectively, there is still a lot of unexplained Real GDP variability as you would expect.

Down the Final Stretch

The final analysis looks at 5 Year data. Statistical tests on this small sample size can be fraught with danger so a table of Real GDP and Equity Returns is presented in Figure 15 below. As mentioned above, all equity returns are calculated in local currency terms; red cells indicate below average results and green cells indicate above average results.

What does all of this mean?

It is important to point out that the analysis in this paper is simplistic insofar that it only looks at quarterly versus quarterly, annual versus annual, 5 yearly versus 5 yearly and considers quarterly and annual lags in equity returns to see if the sharemarket is likely to be a leading indicator. There are many other timeframe permutations that could be tested and the analyses presented in this paper provides no indication as to the true impact of economic news or sharemarket news or the ability to predict stronger or weaker economic outcomes will have on equity market return predictions.

Most importantly, there does appear to be a relationship between Real GDP Growth and Equity returns. There is, however, a big question mark as to what that relationship is because what has been shown in this paper is that the relationship differs between country and across different timeframes and lags.

The sharemarket might be a leading indicator for future economic growth and the ability to predict economic future growth might help predict future equity market returns. But, there are still very large risks of failure involved. At the risk of stating the obvious, there are many other factors to consider, and whilst this paper doesn’t address or compare, valuation metrics are still likely to be a critical factor in the future equity return expectation. That said, whilst the ability to predict future economic growth might not always help in predicting equity market success, it still may provide an edge from time to time.

After a few tough years the Macquarie quant team have decided to upgrade their quantitative models. Looks like they’ve gone to a lot of effort so if they get it wrong again it might be quite fascinating to see how they respond. Anyway, for those who are interested … please click here for their quant-based tips.

Background

When disappointing performance occurs, alarm bells will typically ring in the minds of investors, advisers, asset consultants and perhaps the managers themselves. Investing has only ever been a long game but thanks to the internet, the 24-hour news cycle, social media, etc. etc., it appears that success is expected to occur quickly and this is the case with investing too. Investors have such an enormous selection menu and if one strategy doesn’t appear to be working out then it’s not difficult to find another … and this has been exacerbated with the reduction of transaction costs.

Investment performance has 2 major problems:

Analysis timeframes are too short

Only performance (or benchmark relative performance) is observed

Pure investment performance (or benchmark-relative performance) on a day by day, month by month and even year by year basis is mostly noise and therefore a somewhat redundant analysis exercise. Different styles, risks, industries, sectors, and markets, constantly go in and out of favour and the analysis of performance over these short timeframes is typically a waste of time that can lead to high transaction costs and potentially even worse performance.

The purpose of this article is a simple one. It takes a back-to-basics approach of performance analysis and demonstrates, using a simple case study, one approach of how to cut through the noise to find the signal.

The signal defines what is really happening. The signal is the bigger picture investment view that enables us to undertake better investment analysis, and therefore construct better investment portfolios.

The Short of it

The goal of our case study is to analyse two actively managed Australian equity strategies, renamed to Blue Fund and Orange Fund, to determine their respective suitability for an investment portfolio.

Some quick simple statistics of each fund to begin with…average monthly return and volatility (i.e. standard deviation) over the same time period used in Chart 1 shows the best performer is the Blue Fund, followed by the benchmark, and then the Orange Fund. Low volatility is typically preferred and despite performance volatility has the same order, somewhat counter to the old adage that higher return requires higher risk.

Based on this simple return analysis many would already say that the Blue fund is the superior fund based on the higher level of return per unit of volatility (similar to Sharpe Ratio). However, it is essential to know that Table 1 also suggests that the average monthly returns are not statistically different between both funds and MSCI Australia GR due to the high levels of volatility.

Table 1

This statistical lack of difference between returns is supported by Chart 1 which shows the monthly excess returns of each strategy compared to the MSCI Australia GR index. There is no pattern whatsoever and no one data point is likely t be predictable of the future. Sometimes the Blue fund outperforms the Orange fund and vice versa, and they both outperform the index at different times and vice versa. Thanks to the short time period used for this analysis, i.e. Monthly, this chart provides little to nothing and is a very good demonstration of noise with no obvious sign of a signal.

Chart 1 – Monthly Excess Returns

A Little Longer

The next step in this analysis progression is to increase the period of analysis for each time series data point from monthly to 6 monthly rolling and then 3 year rolling periods. Six months is a common time period used between client portfolio reviews and Chart 2 shows substantial volatility of these 6 monthly excess returns and therefore reasonable evidence alone that any one six-monthly period should not be used to make an investment decision based on performance…and I’m sure that never happens. Six monthly rolling average appears to show no signal for these two funds individually, so the search for a meaningful signal continues.

Chart 2 – 6 Monthly Rolling Average (Annualised) – Excess Returns

On the other hand, potentially there is a signal from Chart 2 which includes timing differences between the Orange and Blue fund’s excess returns. That is, there does appear to be signs where their respective excess returns are moving in opposite directions, plus there are potential signs of the Orange Fund showing more extreme levels of outperformance or underperformance … however, at this point in the analysis these extreme levels should probably be taken with a grain of salt as it has only happened a few times … may be just good or bad luck???

Chart 3, takes the moving average of excess returns out to 3 years and the signals are getting a little stronger. The Orange fund has been a consistent underperformer on rolling 3 year periods since the middle of this time frame.

Anecdotally, 3 years is a popular timeframe for analysis and appears to be the amount of time investors and advisers are prepared to sustain underperformance of any one strategy before changing. The fact the Orange fund has had sustained underperformance over much longer than 3 years suggests that many investors or advisers may have excluded this fund from their consideration set or removed it from portfolios altogether.

However, the Blue Fund is looking very impressive, given very consistent rolling 3-year outperformance through almost the total timeframe so is looking to be the better strategy … or is it?

Chart 3 – 3 Year Rolling Average (Annualised) – Excess Return

Moving on from Pure Performance – Adjusting for Market Risk

Risk-adjusted performance is frequently performed but rightly or wrongly it is rarely done on rolling timeframes and is usually performed across a single chosen time period. Unfortunately a single time period reduces a significant amount of information about investment performance behaviour so the risk-adjusted analysis performed here continues to to be time series based.

The Capital Asset Pricing Model

has a relatively poor reputation for predicting future returns. However, it is an excellent method for calculating exposure to the market (i.e. Beta) and risk-adjusted added value (i.e. Alpha). As we know, all active strategies aim to prove themselves with positive Alpha, which often doubles as the measure that defines “skill”. Using Capital Asset Pricing Model, performance analysis of both funds yields a market-risk-adjusted Alpha over rolling 3 year periods in Chart 4.

Chart 4 shows very different behaviours and potential signals for each fund. Firstly, their respective trends are in relative opposite directions, potentially suggesting opposite style.

The Blue fund has become negative in the earlier years, which wasn’t the case when analysing excess returns so there some currently unknown reasons for its market outperformance, as shown in Chart 3.

The Orange fund continues to show relatively poor results in the latter half of the timeframe, so its still looking like using this analysis many investors may have sold out of the Orange fund given this apparent weak performance.

Chart 4 – 3 Year Rolling Average (Annualised) – CAPM Alpha

Adjusting for Style Risks

The final risk-based performance analysis takes the Capital Asset Pricing Model a step further and introduces other systematic risks into the mathematical model…this model is based on the multi-factor model sometimes called the Arbitrage Pricing Model.

Possibly the most well-known of the multi-factor models is the Fama-French 3 Factor model which adds two risk factors, value and size, to the single risk factor Capital Asset Pricing Model. For the purposes of this analysis, there are 3 additional risk factors which combine MSCI defined indices; Value minus Growth, Small Cap minus Large Cap, and a Momentum risk premium to MSCI Australia benchmark.

Chart 5 shows the Alpha that remains after adjusting for all four risk factors and we can see a dramatic change in result for the Orange Fund. It now has positive Alpha for almost all of the time period analysed, whereas the Blue Fund has a multi-year period of negative Alpha after adjusting for these multiple systematic risks. So whilst the Orange Fund produced underperformance compared to the market in the latter half (refer Chart 3 and/or 4) of this time period, after adjusting for common equity market risk factors, it’s added value (Alpha) is positive. This positive Alpha is what we would want to see from an active manager; positive value-add over and above potentially cheap and replicable systematic risks.

Chart 5 – 3 Year Rolling Average (Annualised) – Multi-Factor Alpha

How did this happen?

So introducing non-market systematic risks improved the Alpha of the Orange Fund and slightly reduced the Alpha of the Blue Fund…how did this happen? The answer is a logical one…one or more of the systematic risks had a significant contribution to the performance of the Orange Fund…and the answer is shown in Chart 6. These two funds have clear distinct styles…the Blue Fund is clearly a Value-style (which MSCI define as holding low PE, low Price/Book, and/or High Dividend securities) and the Orange Fund clearly has a Growth style (which MSCI define as holding stocks with high earnings growth, revenue growth, and internal growth).

So whilst a fund manager may define how they invest with respect to style, deeper performance analysis can show whether that fund does what it says (i.e. is true to label), or can uncover what other risk exposures may be driving good or bad performance. It is worth noting that some qualitative research reports do not specifically define the Orange Fund as a “Growth” fund but given the track record, and the definitions of Growth, it is difficult to argue with the performance analysis.

Chart 6 – 3 Year Rolling Average – Exposure to Value/Growth Factor

Conclusion

The process outlined above will differ from strategy to strategy and will depend on what is important with respect to the role of a potential strategy within a broader portfolio. However, hopefully what this process shows is the significant benefit in undertaking performance analysis that looks through the short term noise that all strategies incur and look for signals using longer timeframes.

To find the signal for constructing better investment portfolios also requires digging deeper into a strategy’s return series. It may involve adjusting performance for multiple risks, such as the market or styles (Value, Growth, Size, Momentum, Quality, Credit, Duration, etc.) whilst still increasing the time period of analysis. Moving away from quarterly or annual performance measures that dominate the industry and survey data is essential. Moving away from analysing performance over short time periods is a positive move that in aggregate will result in superior portfolio performance from lower transaction costs.

The above chart shows the yields for Australian Government Bonds, both nominal bonds and indexed bonds, as at the end of last week (although you can adjust the pricing date to any trading day of 2016). A simple way to determine the market’s inflation expectations over different timeframes is to simply subtract the difference. If you look hover the mouse over each line chart around the maturity date of circa 2020, the difference in yields is in the vicinity of 1.2% to 1.3% … low inflation expectations indeed and certainly a lot lower than the RBA target of 2% to 3%.

So if the RBA achieves its target, then these Australian Government indexed bonds will prove to be pretty reasonable performers … or at least relative to their nominal counterparts. I do know that most of the financial planning industry are still using 2.5% as their inflation target, or at least between 2% and 3% … clearly the market is currently thinking this is way too high and lower inflation than most of us expect should be expected.